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This paper examines the use of evolutionary computation (EC) to find optimal solution in vehicle assignment problem (VAP). The VAP refers to the allocation of the expected number of people in a potentially flooded area to various types of available vehicles in evacuation process. A novel discrete particle swarm optimization (DPSO) algorithm and genetic algorithm (GA) are presented to solve this problem. Both of these algorithms employed a discrete solution representation and incorporated a min-max approach for a random initialization of discrete particle position. A min-max approach is based on minimum capacity and maximum capacity of vehicles. We analyzed the performance of the algorithms using evacuation datasets. The quality of solutions were measured based on the objective function which is to find a maximum number of assigned people to vehicles in the potentially flooded areas and central processing unit (CPU) processing time of the algorithms. Overall, DPSO provides an optimal solutions and successfully achieved the objective function whereas GA gives sub optimal solution for the VAP. [ABSTRACT FROM AUTHOR]

For decades, numerous types of disasters have drawn an array of evacuation planning approaches to support evacuation processes with the objective to minimize total evacuation time. This paper focuses on the construction of optimization evacuation route planning method considering routes and capacity of vehicles. Vehicle Priority Selection (VPS) algorithm was constructed. The formulation of algorithms is based on case study for inundated areas within Kuala Lumpur, Malaysia. Experiments were done on the VPS and the improved VPS algorithm. The improved VPS with prioritize vehicle capacity demonstrates better results compared to other algorithms. It is shown to be applicable for multiple source nodes and large number of evacuees. [ABSTRACT FROM AUTHOR]

Signatures are among the most widely accepted personal attributes for identity verification. There are a lot of features that can be discovered in signature which are either dynamic or static features type. An algorithm needs to be designed to extract these signature features. Online system uses pressure sensitive tablets to capture signature of individual as they sign thus analysis can be done directly and immediately. This research explored slant feature algorithm since signature is usually slanted due to the mechanism of handwriting and the human personality. The proposed algorithm are used to formulate the Signature Extraction Features System (SEFS) which provides a set of tools that allow the users to extract slant features in signature automatically for analysis purposes. Twenty individuals from different background are randomly selected to have their signature taken. Their signatures are captured on a tablet and the SEFS would than gather and store the raw data. The image of the signature that is created by the SEFS would be used as samples for the questionnaire to identify the features of slant, where the questionnaires are given to human expert for evaluation. The results from the SEFS are compared with the result from the questionnaire. Results produced by the algorithm for slant extraction shows 85% identical answers compared to the outcome by human expert. These show that the algorithm proposed are promising for further exploration. [ABSTRACT FROM AUTHOR]

Due to difficulty in monitoring the attendance of members in the higher education institution (HEI), the HEI management has recognized the need to conduct a study on the adoption of fingerprint system. The study identified the appropriate indexing model and developed a questionnaire that suits for the environment. The higher education institution selected for this study is International Islamic University Malaysia (IIUM). The target groups were selected across a sample of the organisation΄s members. The returned questionnaires were analyzed using a standard statistical tool. Reliability and normality testing were deployed to ensure that the data is reliable and normal for further testing. Spearman΄s correlation and Kruskal Wallis were used to find the relation between elements of innovativeness, optimism, discomfort and insecurity. The findings have revealed that the innovativeness and optimism have a positive relation with the users΄ readiness. Meanwhile, discomfort and insecurity gave a negative relation to the faculty members΄. This indicates that the faculty member is aware of the technology and optimist with the implementation of the technology in their organization. However, they still feel insecure and discomfort with the justification and impact of the implementation. [ABSTRACT FROM AUTHOR]

Controlling the amount of water in maintaining lawn health and beauty is a main topic in horticulture. A reliable controller is needed to control the amount of water to disperse as to ensure the soil has enough moisture adequacy level. This research explores the use of fuzzy logic for the controlling of water dispersal. The performances of fuzzy water dispersal controller (FuziWDC) was measured based on a significant set of common Bermuda turfgrass. An improved Sugeno inferencing for the task of water dispersal controller is presented that considered both evapotranspiration (ET), tensiometer variable as opposed to the earlier work. A comparison of the output is being performed to evaluate Sugeno with conventional system. The result shows FuziWDC has performed better than the conventional technique based on the lower annual average water usage for the whole year recorded. [ABSTRACT FROM AUTHOR]